Create RabbitMQ queues, exchanges, and bindings from Kubernetes Custom Resources.
npx skills add https://github.com/eco2-team/backend --skill celery-rabbitmq
Please help me install this Agent Skill. Skill: celery-rabbitmq Source: https://github.com/eco2-team/backend/tree/main/.claude/skills/celery-rabbitmq Command: npx skills add https://github.com/eco2-team/backend --skill celery-rabbitmq
It solves the manual burden of configuring Celery task routing by moving queue, exchange, and binding creation to Kubernetes Custom Resources, ensuring deterministic topology and avoiding runtime declarations in code.
Prepare your cluster with the RabbitMQ operator, create Queue/Exchange/Binding CRs under workloads/rabbitmq/base/topology, configure Celery task_routes and task_queues in apps/<worker>/setup/celery.py, then deploy workers and verify queues exist in RabbitMQ.
High-intent search queries and answers about installing and using this skill.
You can declare Celery RabbitMQ queues and exchanges by defining Kubernetes Custom Resources for topology, letting the RabbitMQ operator materialize them automatically. This removes manual runtime declarations and ensures deterministic queue and exchange creation across deployments.
Celery task routing breaks from manual RabbitMQ queue configuration due to runtime declaration inconsistencies. Moving queue, exchange, and binding creation to Kubernetes Custom Resources enforces deterministic topology, preventing routing mismatches and ensuring predictable deployments.
Yes, you can manage dead-letter queues for Celery tasks through Kubernetes Custom Resources. The topology configuration includes built-in DLQ support, allowing the operator to handle dead-letter routing automatically without manual RabbitMQ intervention.
Configuring Celery queue topology via Kubernetes CRDs separates routing logic from infrastructure by keeping task_routes in Python code while moving queue, exchange, and binding definitions to the Kubernetes layer. This ensures clean separation of concerns across environments.
Deploy a multi-tenant Celery application with dedicated RabbitMQ queues by creating Queue, Exchange, and Binding Custom Resources per service. Configure task_routes in your worker setup, then deploy workers to let the operator materialize topology with dead-letter handling.
Yes, you need the RabbitMQ operator installed in your Kubernetes cluster to use declarative queue topology for Celery workers. The operator reads your Queue, Exchange, and Binding Custom Resources and materializes them in the RabbitMQ cluster.
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